in this article, multichannel eeg signals of artists and nonartists were analyzed during the performances of visual perception and mental imagery of paintings using cepstrum coefficients. each of the calculated cepstrum coefficients and their parameters such as energy, average, standard deviation and entropy were separately used for distinguishing the two groups. it was also found that a distin...

Different types of cepstral analysis are compared in the context of a percussion instrument classification external for Pd. For raw cepstrum, mel frequency cepstrum, DCT-based cepstrum, and bark frequency cepstrum, various parameter settings are applied to a standardized test. Significant score improvement can be seen when moving from cepstrum to mel cepstrum, and further improvement is achieve...

A new modification of the LPC cepstrum of speech signal called clipped LPC (CLPC) cepstrum is proposed. In the CLPC cepstrum is reduced the influence of the low level LPC spectrum’s regions. Three LPC cepstrums as features in a textindependent speaker identification task were evaluated using reading text in Bulgarian language collected over noisy telephone lines. These cepstrums are: standard L...

It is not widely realised that the first paper on cepstrum analysis was published two years before the FFT algorithm, despite having Tukey as a common author, and its definition was such that it was not reversible even to the log spectrum. After publication of the FFT in 1965, the cepstrum was redefined so as to be reversible to the log spectrum, and shortly afterwards Oppenheim and Schafer def...

In this paper, we propose a novel data hiding scheme for audio signals in cepstrum domain. Cepstrum representation of audio can be shown to be very robust to a wide range of attacks including most challenging time-scaling and pitch-shifting warping. In cepstrum domain, we propose to embed data by manipulating statistical mean of selected cepstrum coefficients. An intuitive psychoacoustic model ...

A multitask convolutional neural network (CNN) is trained to localize the instantaneous position of a motorboat throughout its transit past wide aperture linear array hydrophones located 1 m above sea floor in water 20 deep. cepstrogram database for each hydrophone and cross-correlogram pair adjacent are compiled multiple transits. Cepstrum-based correlation-based feature vectors (along with gr...

The basic goal of the voice conversion system to mimics the characteristics of the target speaker voice by keeping the linguistic and paralinguistic information intact. The characteristics of a speaker in speech reflect at different level such as vocal tract, excitation and prosodic parameters. This propose work based on cepstrum which represents the vocal tract and excitation parameters of the...

Cepstrum is an algorithm for analyzing the speech signals in frequency domain. This is conventional method of fundamental peak picking i.e. fundamental frequency or pitch. For a speech signal it is necessary to identify the fundamental frequency correctly in order to have robust system for speaker identification and verification. Using this approach two algorithms has been proposed using Hammin...

Cepstral normalisation in automatic speech recognition is investigated in the context of robustness to additive noise. In this paper, it is argued that such normalisation leads naturally to a speech feature based on signal to noise ratio rather than absolute energy (or power). Explicit calculation of this SNR-cepstrum by means of a noise estimate is shown to have theoretical and practical advan...